Diane Arbus: the wonderful wizard of odds or the poetics of the i (eye)

Diane Arbus‘ photographs are mainly about difference. Most of the time she is trying ‗[…] to suppress, or at least reduce, moral and sensory queasiness‘ (Sontag 1977: 40) in order to represent a world where the subject of the photograph is not merely the ‗other‘ but also the I. Her technique does not coax her subjects into natural poses. Instead she encourages them to be strange and awkward. By posing for her, the revelation of the self is identified with what is odd. This paper aims at understanding the geography of difference that, at the same time, is also of resistance, since Diane Arbus reveals what was forcefully hidden by bringing it into light in such a way that it is impossible to ignore. Her photographs display a poetic beauty that is not only of the ‗I‘ but also of the ‗eye‘. The world that is depicted is one in which we are all the same. She ―atomizes‖ reality by separating each element and ‗Instead of showing identity between things which are different […] everybody is shown to look the same.‘ (Sontag 1977: 47). Furthermore, this paper analyses some of Arbus‘ photographs so as to explain this point of view, by trying to argue that between rejecting and reacting against what is standardized she does not forget the geography of the body which is also a geography of the self. While creating a new imagetic topos, where what is trivial becomes divine, she also presents the frailty of others as our own.

A fuzzified systematic adjustment of the robotic Darwinian PSO

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization using natural selection to enhance the ability to escape from sub-optimal solutions. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots, hence decreasing the amount of required information exchange among robots. This paper further extends the previously proposed algorithm adapting the behavior of robots based on a set of context-based evaluation metrics. Those metrics are then used as inputs of a fuzzy system so as to systematically adjust the RDPSO parameters (i.e., outputs of the fuzzy system), thus improving its convergence rate, susceptibility to obstacles and communication constraints. The adapted RDPSO is evaluated in groups of physical robots, being further explored using larger populations of simulated mobile robots within a larger scenario.